There is a vital interest in many picture processing workflows, both for motion and still pictures, to objectively and efficiently measure, visualize and evaluate the quality of the picture in terms of sharpness. E.g. in image production workflows, production content can be evaluated at different stages down the line. The sharpness of an image is a matter of edge contrast and resolution. Image sharpness and contrast are important in differed domains of vision, e.g. human perception, image processing, image acquisition and image display. Generally, contrast is a measure of the difference between the darkest and brightest spot within an image. Different metrics for evaluating contrast in different applications are known. Most of them make prior assumptions about the image content. Known contrast types are e.g. Weber contrast, Michelson contrast and Root-Mean-Square (RMS) contrast. However, no solution is known for automatically determining a sharpness metric of an image. In particular, it would be desirable for various applications to express such sharpness metric as a numeric value.